Data processing systems for fulfilling data subject access requests and related methods

ABSTRACT

In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization&#39;s systems, the system may: (1) automatically determine where the data subject&#39;s personal data is stored; and (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject&#39;s personal data from the various systems (e.g., by automatically assigning a plurality of tasks to delete data across multiple business systems to effectively delete the data subject&#39;s personal data from the systems).

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/659,437, filed Oct. 21, 2019, which is a continuation-in-part of U.S.patent application Ser. No. 16/410,566, filed May 13, 2019, now U.S.Pat. No. 10,452,866, issued Oct. 22, 2019, which is acontinuation-in-part of U.S. patent application Ser. No. 16/055,083,filed Aug. 4, 2018, now U.S. Pat. No. 10,289,870, issued May 14, 2019,which claims priority from U.S. Provisional Patent Application Ser. No.62/547,530, filed Aug. 18, 2017, and is also a continuation-in-part ofU.S. patent application Ser. No. 15/996,208, filed Jun. 1, 2018, nowU.S. Pat. No. 10,181,051, issued Jan. 15, 2019, which claims priorityfrom U.S. Provisional Patent Application Ser. No. 62/537,839, filed Jul.27, 2017, and is also a continuation-in-part of U.S. patent applicationSer. No. 15/853,674, filed Dec. 22, 2017, now U.S. Pat. No. 10,019,597,issued Jul. 10, 2018, which claims priority from U.S. Provisional PatentApplication Ser. No. 62/541,613, filed Aug. 4, 2017, and is also acontinuation-in-part of U.S. patent application Ser. No. 15/619,455,filed Jun. 10, 2017, now U.S. Pat. No. 9,851,966, issued Dec. 26, 2017,which is a continuation-in-part of U.S. patent application Ser. No.15/254,901, filed Sep. 1, 2016, now U.S. Pat. No. 9,729,583, issued Aug.8, 2017, which claims priority from: (1) U.S. Provisional PatentApplication Ser. No. 62/360,123, filed Jul. 8, 2016; (2) U.S.Provisional Patent Application Ser. No. 62/353,802, filed Jun. 23, 2016;and (3) U.S. Provisional Patent Application Ser. No. 62/348,695, filedJun. 10, 2016. The disclosures of all of the above patent applicationsand patents are hereby incorporated herein by reference in theirentirety.

BACKGROUND

Over the past years, privacy and security policies, and relatedoperations have become increasingly important. Breaches in security,leading to the unauthorized access of personal data (which may includesensitive personal data) have become more frequent among companies andother organizations of all sizes. Such personal data may include, but isnot limited to, personally identifiable information (PII), which may beinformation that directly (or indirectly) identifies an individual orentity. Examples of PII include names, addresses, dates of birth, socialsecurity numbers, and biometric identifiers such as a person'sfingerprints or picture. Other personal data may include, for example,customers' Internet browsing habits, purchase history, and even theirpreferences (e.g., likes and dislikes, as provided or obtained throughsocial media).

Many organizations that obtain, use, and transfer personal data,including sensitive personal data, have begun to address these privacyand security issues. To manage personal data, many companies haveattempted to implement operational policies and processes that complywith legal and organizations, or other entities) with certain rightsrelated to the data subject's personal data that is collected, stored,or otherwise processed by an organization. These rights may include, forexample, a right to obtain confirmation of whether a particularorganization is processing their personal data, a right to obtaininformation about the purpose of the processing (e.g., one or morereasons for which the personal data was collected), and other suchrights. Some regulations require organizations to comply with requestsfor such information (e.g., Data Subject Access Requests) withinrelatively short periods of time (e.g., 30 days).

Existing systems for complying with such requests can be inadequate forproducing and providing the required information within the requiredtimelines. This is especially the case for large corporations, which maystore data on several different platforms in differing locations.Accordingly, there is a need for improved systems and methods forcomplying with data subject access requests.

SUMMARY

A computer-implemented method, according to various embodiments, forreceiving data subject access requests (DSAR's) via multiple websitesand managing the data subject access requests, comprises: (1)presenting, by at least one computer processor, a first webform on afirst website, the first webform being adapted to receive data subjectaccess requests and to route the requests to a first designatedindividual for processing; (2) presenting, by at least one computerprocessor, a second webform on a second website, the second webformbeing adapted to receive data subject access requests and to route therequests to a second designated individual for processing; (3)receiving, by at least one computer processor, via the first webform, afirst data subject access request; (4) at least partially in response tothe receiving the first data subject access request, automaticallyrouting the first data subject access request to the first designatedindividual for handling; and (5) at least partially in response to thereceiving the second data subject access request, automatically routingthe second data subject access request to the second designatedindividual for handling.

A computer system for receiving data subject access requests via awebform and automatically processing the requests, according to variousembodiments, comprises: (1) one or more computer processors; and (2)computer memory operatively coupled to the one or more processors,wherein the one or more computer processors are adapted to: (A) presenta webform on a website, the webform being adapted to receive datasubject access requests and to route the requests to a designatedindividual for processing; (B) receiving, via the webform, a datasubject access request from a data subject access requestor; and (C) atleast partially in response to the receiving the data subject accessrequest, automatically processing the data subject access request.

A computer-implemented method for prioritizing a plurality of datasubject access requests, according to particular embodiments, comprises:(1) receiving a data subject access request; (2) at least partially inresponse to receiving the data subject access request, obtainingmetadata regarding a data subject of the data subject access request;and (3) using the metadata to determine whether a priority of the DSARshould be adjusted based on the obtained metadata; and in response todetermining that the priority of the DSAR should be adjusted based onthe obtained metadata, adjusting the priority of the DSAR.

A computer-implemented method for processing a request to delete a datasubject's personal data from one or more computer systems of anorganization, according to various embodiments, comprises: (1)receiving, by one or more computer processors, a request from a datasubject to delete the data subject's personal data from one or morecomputer systems of an organization; (2) at least partially in responseto receiving the request: (A) automatically identifying, by one or morecomputer processors, one or more computing devices on which the datasubject's personal data is stored; and (B) in response to determining,by one or more computer processors, the location of the data subject'spersonal data, automatically facilitating the deletion of (e.g.,deleting) the data subject's personal data from the one or morecomputing devices.

The following is listing of various additional concepts according tovarious embodiments:

Concept 1. A non-transitory computer-readable medium storingcomputer-executable instructions for processing a request to deletepersonal data from a plurality of computing devices associated with aparticular organization by:

-   -   receiving a plurality of delete personal data requests, each        delete personal data request being a request, from a respective        data subject, to delete personal data associated with the data        subject; and    -   at least partially in response to receiving each respective        delete personal data request:        -   automatically using a data model to identify: (A) a first            computing device on which first respective personal data            associated with the respective data subject is stored;            and (B) a second computing device on which second respective            personal data associated with the respective data subject is            stored, wherein:        -   the data model defines:            -   at least one storage location utilized in the storage of                a plurality of different items of personal data for the                data subject as part of a processing activity; and at                least one transfer location to which the plurality of                different items of personal data for the data subject                are transferred; and        -   automatically using the data model to identify the first            computing device and the second computing device            comprises: (A) using a unique identifier associated with the            data subject in combination with the data model to identify            the first computing device as storing the first respective            personal data associated with the respective data subject;            and (B) using the unique identifier associated with the data            subject in combination with the data model to identify the            second computing device as storing the second respective            personal data associated with the respective data subject;    -   at least partially in response to identifying the first        computing device as storing the first respective personal data        associated with the respective data subject, facilitating the        deletion of the first respective personal data from the first        computing device; and    -   at least partially in response to identifying the second        computing device as storing the second respective personal data        associated with the respective data subject, facilitating the        deletion of the second respective personal data from the second        computing device, wherein:

the data model stores information regarding respective storage locationsof the plurality of different items of personal data for the datasubject.

Concept 2. The non-transitory computer-readable medium of Concept 1,wherein the non-transitory computer-readable medium storescomputer-executable instructions for concurrently processing at leastfive of the plurality of delete personal data requests in an automatedmanner.

Concept 3. The non-transitory computer-readable medium of Concept 2,wherein the data model stores information regarding respective storagelocations of a plurality of different respective items of personal datafor each of a plurality of individuals other than the data subject.

Concept 4. The non-transitory computer-readable medium of Concept 1,wherein the non-transitory computer-readable medium storescomputer-executable instructions for facilitating the execution ofmultiple delete personal data requests in response to a single commandfrom a user.

Concept 5. The non-transitory computer-readable medium of Concept 1,wherein the non-transitory computer-readable medium storescomputer-executable instructions for facilitating the concurrentexecution of multiple delete personal data requests in response to asingle command from a user.

Concept 6. The non-transitory computer-readable medium of Concept 1,wherein the non-transitory computer-readable medium storescomputer-executable instructions for:

automatically verifying an identity of the respective data subject; and

at least partially in response to verifying the identity of therespective data subject, processing the respective delete personal datarequest.

Concept 7. The non-transitory computer-readable medium of Concept 1,wherein the non-transitory computer-readable medium storescomputer-executable instructions for:

-   -   at least partially in response to receiving each respective        delete personal data request, obtaining metadata regarding the        respective data subject;    -   using the metadata to determine whether a priority of the        respective request should be adjusted based on the obtained        metadata; and    -   in response to determining that the priority of the respective        request should be adjusted based on the obtained metadata,        adjusting the priority of the respective request, wherein the        metadata comprises metadata selected from a group consisting        of: (A) a location from which the respective request was        made; (B) one or more current sensitivities to world events;        and (C) a status of the data subject; and    -   fulfilling the respective request according to the adjusted        priority of the respective request.

Concept 8. The non-transitory computer-readable medium of Concept 7,wherein the metadata comprises a location from which the respectiverequest was made.

Concept 9. The non-transitory computer-readable medium of Concept 7,wherein the metadata comprises a status of the respective data subject.

Concept 10. The non-transitory computer-readable medium of Concept 1,wherein each of the first and second computing devices is associatedwith a different respective corporate entity of a plurality of corporateentities.

Concept 11. The non-transitory computer-readable medium of Concept 10,wherein the plurality of corporate entities are sub-organizations of theparticular organization.

Concept 12. A computer-implemented data processing method for processingrequests to delete personal data associated with respective datasubjects from one or more computer systems of an organization, themethod comprising:

receiving, by one or more computer processors, a plurality of deletepersonal data requests, each delete personal data request being arequest, from a respective data subject, to delete personal dataassociated with the data subject; and

at least partially in response to receiving each respective request ofthe plurality of requests:

-   -   automatically identifying, by one or more computer processors,        one or more computing devices of the one or more computer        systems on which the personal data associated with the        respective data subject is stored, wherein identifying the one        or more computing devices on which the personal data associated        with the respective data subject is stored comprises:        -   accessing, by one or more computer processors, a data model            defining:            -   at least one storage location where a plurality of                pieces of personal data are stored as part of a                processing activity;            -   at least one transfer location to which the plurality of                pieces of personal data are transferred from the at                least one storage location as part of the processing                activity; and        -   using a unique identifier associated with the data subject,            in combination with the data model, to identify the personal            data associated with the respective data subject; and

in response to identifying, by one or more computer processors, the oneor more computing devices on which the personal data associated with therespective data subject is stored, automatically facilitating thedeletion of the personal data associated with the respective datasubject from the one or more computing devices.

Concept 13. The computer-implemented data processing method of Concept12, wherein the method further comprises concurrently processing, by oneor more computer processors, at least five of the plurality of deletepersonal data requests in an automated manner.

Concept 14. The computer-implemented data processing method of Concept12, wherein automatically facilitating the deletion of the personal dataassociated with the respective data subject from the one or morecomputing devices comprises overwriting the personal data associatedwith the respective data subject in computer memory associated with theone or more computing devices.

Concept 15. The computer-implemented data processing method of Concept12, wherein facilitating the deletion of the personal data associatedwith the respective data subject from the one or more computing devicescomprises facilitating the deletion of the respective data subject'spersonal data from both the at least one storage location and the atleast one transfer location.

Concept 16. The computer-implemented data processing method of Concept12, wherein the unique identifier associated with the data subjectcomprises a unique identifier generated in response to receiving consentfrom the respective data subject for the initial storage of the personaldata associated with the respective data subject as part of theprocessing activity.

Concept 17. The computer-implemented data processing method of Concept12, wherein identifying one or more computing devices of the one or morecomputer systems on which the personal data associated with therespective data subject is stored comprises identifying the one or morecomputing devices using one or more data modeling means.

Concept 18. The computer-implemented data processing method of Concept12, wherein the method further comprises:

identifying a first processing activity under which the respective datasubject has previously provided consent for the collection of personaldata; and

electronically accessing a first data inventory associated with thefirst processing activity, the first data inventory identifying:

-   -   a first data asset of the one or more computer systems on which        the personal data collected as part of the first processing        activity is stored;    -   transfer data associated with the first data asset; and    -   access data associated with the first data asset; and

facilitating the deletion of the personal data associated with therespective data subject from the one or more computing devices by:

-   -   automatically assigning a first task to delete the personal data        associated with the respective data subject from the first data        asset;    -   identifying a second data asset based at least in part on the        transfer data;    -   automatically assigning a second task to delete the personal        data associated with the respective data subject from the second        data asset;    -   identifying a third data asset based at least in part on the        access data; and    -   automatically assigning a third task to delete the personal data        associated with the respective data subject from the third data        asset.

Concept 19. A computer-implemented data processing method for deletingone or more pieces of personal data in response to a data subject accessrequest, the method comprising:

receiving, using one or more electronic receiving means, a data subjectaccess request from a requestor comprising one or more requestparameters;

accessing, using one or more electronic access means, a data modeldefining:

-   -   at least one storage location utilized in the storage of a        plurality of pieces of personal data as part of a processing        activity; and    -   at least one transfer location to which the plurality of pieces        of personal data are transferred, wherein the data model        comprises information regarding a respective storage location of        each of one or more pieces of personal data associated with the        requestor;

using the data model and a unique identifier associated with therequestor to identify the respective storage location of each of the oneor more pieces of personal data associated with the requestor, the oneor more pieces of personal data being stored in one or more datarepositories associated with a particular organization;

determining whether the one or more request parameters comprise arequest to delete the one or more pieces of personal data; and

in response to determining that the one or more request parameterscomprise the request to delete, automatically facilitating the deletion,using one or more data deletion means, of the one or more pieces ofpersonal data.

Concept 20. The computer-implemented data processing method of Concept19, wherein:

the method further comprises identifying, using one or more consentreceipt management means, one or more processing activities undertakenby the particular organization that involve the storage of the one ormore pieces of personal data; and

processing the request further comprises identifying the respectivestorage location of each of the one or more pieces of personal databased at least in part on storage data associated with the one or moreprocessing activities.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of a data subject access request fulfillment systemare described below. In the course of this description, reference willbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 depicts a data subject request processing and fulfillment systemaccording to particular embodiments.

FIG. 2A is a schematic diagram of a computer (such as the data modelgeneration server 110, or data model population server 120 of FIG. 1)that is suitable for use in various embodiments of the data subjectrequest processing and fulfillment system shown in FIG. 1.

FIG. 2B is a flow chart depicting exemplary steps executed by a DataSubject Access Request Routing Module according to a particularembodiment

FIGS. 3-43 are computer screen shots that demonstrate the operation ofvarious embodiments.

FIGS. 44-49 depict various exemplary screen displays and user interfacesthat a user of various embodiments of the system may encounter (FIGS. 47and 48 collectively show four different views of a Data Subject RequestQueue).

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings. It should be understood that theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein. Rather, theseembodiments are provided so that this disclosure will be thorough andcomplete, and will fully convey the scope of the invention to thoseskilled in the art. Like numbers refer to like elements throughout.

Overview

Ticket management systems, according to various embodiments, are adaptedto receive data subject access requests (DSAR's) from particular datasubjects, and to facilitate the timely processing of valid DSAR's by anappropriate respondent. In particular embodiments, the ticket managementsystem receives DSAR's via one or more webforms that each may, forexample, respectively be accessed via an appropriate link/button on arespective web page. In other embodiments, the system may receive DSAR'sthrough any other suitable mechanism, such as via a computer softwareapplication (e.g., a messaging application such as Slack, Twitter), viaa chat bot, via generic API input from another system, or through entryby a representative who may receive the information, for example, viasuitable paper forms or over the phone.

The ticket management system may include a webform creation tool that isadapted to allow a user to create customized webforms for receivingDSAR's from various different data subject types and for routing therequests to appropriate individuals for processing. The webform creationtool may, for example, allow the user to specify the language that theform will be displayed in, what particular information is to berequested from the data subject and/or provided by the data subject, whoany DSAR's that are received via the webform will be routed to, etc. Inparticular embodiments, after the user completes their design of thewebform, the webform creation tool generates code for the webform thatmay be cut and then pasted into a particular web page.

The system may be further adapted to facilitate processing of DSAR'sthat are received via the webforms, or any other suitable mechanism. Forexample, the ticket management system may be adapted to execute one ormore of the following steps for each particular DSAR received via thewebforms (or other suitable mechanism) described above: (1) beforeprocessing the DSAR, confirm that the DSAR was actually submitted by theparticular data subject of the DSAR (or, for example, by an individualauthorized to make the DSAR on the data subject's behalf, such as aparent, guardian, power-of-attorney holder, etc.)—any suitable methodmay be used to confirm the identity of the entity/individual submittingthe DSAR—for example, if the system receives the DSAR via a third-partycomputer system, the system may validate authentication via API secret,or by requiring a copy of one or more particular legal documents (e.g.,a particular contract between two particular entities)—the system mayvalidate the identity of an individual by, for example, requiring theindividual (e.g., data subject) to provide particular accountcredentials, by requiring the individual to provide particularout-of-wallet information, through biometric scanning of the individual(e.g., finger or retinal scan), or via any other suitable identityverification technique; (2) if the DSAR was not submitted by theparticular data subject, deny the request; (3) if the DSAR was submittedby the particular data subject, advance the processing of the DSAR; (4)route the DSAR to the correct individual(s) or groups internally forhandling; (5) facilitate the assignment of the DSAR to one or more otherindividuals for handling of one or more portions of the DSAR; (6)facilitate the suspension of processing of the data subject's data bythe organization; and/or (7) change the policy according to which thedata subject's personal data is retained and/or processed by the system.In particular embodiments, the system may perform any one or more of theabove steps automatically. The system then generates a receipt for theDSAR request that the user can use as a transactional record of theirsubmitted request.

In particular embodiments, the ticket management system may be adaptedto generate a graphical user interface (e.g., a DSAR request-processingdashboard) that is adapted to allow a user (e.g., a privacy officer ofan organization that is receiving the DSAR) to monitor the progress ofany of the DSAR requests. The GUI interface may display, for each DSAR,for example, an indication of how much time is left (e.g., quantified indays and/or hours) before a legal and/or internal deadline to fulfillthe request. The system may also display, for each DSAR, a respectiveuser-selectable indicium that, when selected, may facilitate one or moreof the following: (1) verification of the request; (2) assignment of therequest to another individual; (3) requesting an extension to fulfillthe request; (4) rejection of the request; or (5) suspension of therequest.

As noted immediately above, and elsewhere in this application, inparticular embodiments, any one or more of the above steps may beexecuted by the system automatically. As a particular example, thesystem may be adapted to automatically verify the identity of the DSARrequestor and then automatically fulfill the DSAR request by, forexample, obtaining the requested information via a suitable data modeland communicating the information to the requestor. As anotherparticular example, the system may be configured to automatically routethe DSAR to the correct individual for handling based at least in parton one or more pieces of information provided (e.g., in the webform).

In various embodiments, the system may be adapted to prioritize theprocessing of DSAR's based on metadata about the data subject of theDSAR. For example, the system may be adapted for: (1) in response toreceiving a DSAR, obtaining metadata regarding the data subject; (2)using the metadata to determine whether a priority of the DSAR should beadjusted based on the obtained metadata; and (3) in response todetermining that the priority of the DSAR should be adjusted based onthe obtained metadata, adjusting the priority of the DSAR.

Examples of metadata that may be used to determine whether to adjust thepriority of a particular DSAR include: (1) the type of request; (2) thelocation from which the request is being made; (3) the country ofresidency of the data subject and, for example, that county's tolerancefor enforcing DSAR violations; (4) current sensitivities to worldevents; (5) a status of the requestor (e.g., especially loyal customer);or (6) any other suitable metadata.

Exemplary Technical Platforms

As will be appreciated by one skilled in the relevant field, the presentinvention may be, for example, embodied as a computer system, a method,or a computer program product. Accordingly, various embodiments may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, or an embodiment combining software and hardware aspects.Furthermore, particular embodiments may take the form of a computerprogram product stored on a computer-readable storage medium havingcomputer-readable instructions (e.g., software) embodied in the storagemedium. Various embodiments may take the form of web-implementedcomputer software. Any suitable computer-readable storage medium may beutilized including, for example, hard disks, compact disks, DVDs,optical storage devices, and/or magnetic storage devices.

Various embodiments are described below with reference to block diagramsand flowchart illustrations of methods, apparatuses (e.g., systems), andcomputer program products. It should be understood that each block ofthe block diagrams and flowchart illustrations, and combinations ofblocks in the block diagrams and flowchart illustrations, respectively,can be implemented by a computer executing computer programinstructions. These computer program instructions may be loaded onto ageneral-purpose computer, special-purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus to create means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner such that the instructions stored in the computer-readable memoryproduce an article of manufacture that is configured for implementingthe function specified in the flowchart block or blocks. The computerprogram instructions may also be loaded onto a computer or otherprogrammable data processing apparatus to cause a series of operationalsteps to be performed on the computer or other programmable apparatus toproduce a computer implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide stepsfor implementing the functions specified in the flowchart block orblocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of mechanisms for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instructions for performing the specified functions. Itshould also be understood that each block of the block diagrams andflowchart illustrations, and combinations of blocks in the blockdiagrams and flowchart illustrations, can be implemented by specialpurpose hardware-based computer systems that perform the specifiedfunctions or steps, or combinations of special purpose hardware andother hardware executing appropriate computer instructions.

Example System Architecture

FIG. 1 is a block diagram of a data subject access request processingand fulfillment system 100 according to a particular embodiment. Invarious embodiments, the data subject access request processing andfulfillment system is part of a privacy compliance system (also referredto as a privacy management system), or other system, which may, forexample, be associated with a particular organization and be configuredto aid in compliance with one or more legal or industry regulationsrelated to the collection and storage of personal data.

As may be understood from FIG. 1, the data subject access requestprocessing and fulfillment system 100 includes one or more computernetworks 115, a Data Model Generation Server 110, a Data ModelPopulation Server 120, an Intelligent Identity Scanning Server 130(which may automatically validate a DSAR requestor's identity), One orMore Databases 140 or other data structures, one or more remotecomputing devices 150 (e.g., a desktop computer, laptop computer, tabletcomputer, smartphone, etc.), and One or More Third Party Servers 160. Inparticular embodiments, the one or more computer networks 115 facilitatecommunication between the Data Model Generation Server 110, Data ModelPopulation Server 120, Intelligent Identity Scanning/Verification Server130, One or More Databases 140, one or more remote computing devices 150(e.g., a desktop computer, laptop computer, tablet computer, smartphone,etc.), One or More Third Party Servers 160, and DSAR Processing andFulfillment Server 170. Although in the embodiment shown in FIG. 1, theData Model Generation Server 110, Data Model Population Server 120,Intelligent Identity Scanning Server 130, One or More Databases 140, oneor more remote computing devices 150 (e.g., a desktop computer, laptopcomputer, tablet computer, smartphone, etc.), and One or More ThirdParty Servers 160, and DSAR Processing and Fulfillment Server 170 areshown as separate servers, it should be understood that in otherembodiments, the functionality of one or more of these servers and/orcomputing devices may, in different embodiments, be executed by a largeror smaller number of local servers, one or more cloud-based servers, orany other suitable configuration of computers.

The one or more computer networks 115 may include any of a variety oftypes of wired or wireless computer networks such as the Internet, aprivate intranet, a public switch telephone network (PSTN), or any othertype of network. The communication link between the DSAR Processing andFulfillment Server 170 and the One or More Remote Computing Devices 150may be, for example, implemented via a Local Area Network (LAN) or viathe Internet. In other embodiments, the One or More Databases 140 may bestored either fully or partially on any suitable server or combinationof servers described herein.

FIG. 2A illustrates a diagrammatic representation of a computer 200 thatcan be used within the data subject access request processing andfulfillment system 100, for example, as a client computer (e.g., one ormore remote computing devices 150 shown in FIG. 1), or as a servercomputer (e.g., Data Model Generation Server 110 shown in FIG. 1). Inparticular embodiments, the computer 200 may be suitable for use as acomputer within the context of the data subject access requestprocessing and fulfillment system 100 that is configured for routingand/or processing DSAR requests and/or generating one or more datamodels used in automatically fulfilling those requests.

In particular embodiments, the computer 200 may be connected (e.g.,networked) to other computers in a LAN, an intranet, an extranet, and/orthe Internet. As noted above, the computer 200 may operate in thecapacity of a server or a client computer in a client-server networkenvironment, or as a peer computer in a peer-to-peer (or distributed)network environment. The Computer 200 may be a personal computer (PC), atablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), acellular telephone, a web appliance, a server, a network router, aswitch or bridge, or any other computer capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that computer. Further, while only a single computer is illustrated,the term “computer” shall also be taken to include any collection ofcomputers that individually or jointly execute a set (or multiple sets)of instructions to perform any one or more of the methodologiesdiscussed herein.

An exemplary computer 200 includes a processing device 202, a mainmemory 204 (e.g., read-only memory (ROM), flash memory, dynamic randomaccess memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM(RDRAM), etc.), static memory 206 (e.g., flash memory, static randomaccess memory (SRAM), etc.), and a data storage device 218, whichcommunicate with each other via a bus 232.

The processing device 202 represents one or more general-purposeprocessing devices such as a microprocessor, a central processing unit,or the like. More particularly, the processing device 202 may be acomplex instruction set computing (CISC) microprocessor, reducedinstruction set computing (RISC) microprocessor, very long instructionword (VLIW) microprocessor, or processor implementing other instructionsets, or processors implementing a combination of instruction sets. Theprocessing device 202 may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like. The processing device 202 may beconfigured to execute processing logic 226 for performing variousoperations and steps discussed herein.

The computer 120 may further include a network interface device 208. Thecomputer 200 also may include a video display unit 210 (e.g., a liquidcrystal display (LCD) or a cathode ray tube (CRT)), an alphanumericinput device 212 (e.g., a keyboard), a cursor control device 214 (e.g.,a mouse), and a signal generation device 216 (e.g., a speaker).

The data storage device 218 may include a non-transitorycomputer-accessible storage medium 230 (also known as a non-transitorycomputer-readable storage medium or a non-transitory computer-readablemedium) on which is stored one or more sets of instructions (e.g.,software instructions 222) embodying any one or more of themethodologies or functions described herein. The software instructions222 may also reside, completely or at least partially, within mainmemory 204 and/or within processing device 202 during execution thereofby computer 200-main memory 204 and processing device 202 alsoconstituting computer-accessible storage media. The softwareinstructions 222 may further be transmitted or received over a network115 via network interface device 208.

While the computer-accessible storage medium 230 is shown in anexemplary embodiment to be a single medium, the term“computer-accessible storage medium” should be understood to include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore sets of instructions. The terms “computer-accessible storagemedium”, “computer-readable medium”, and like terms should also beunderstood to include any medium that is capable of storing, encoding orcarrying a set of instructions for execution by the computer and thatcause the computer to perform any one or more of the methodologies ofthe present invention. These terms should accordingly be understood toinclude, but not be limited to, solid-state memories, optical andmagnetic media, etc.

Systems for Managing Data Subject Access Requests

In various embodiments, the system may include a ticket managementsystem and/or other systems for managing data subject access requests.In operation, the system may use one or more computer processors, whichare operatively coupled to memory, to execute one or more softwaremodules (which may be included in the Instructions 222 referenced above)such as: (1) a DSAR Request Routing Module 1000; and (4) a DSARPrioritization Module. An overview of the functionality and operation ofeach of these modules is provided below.

Data Subject Access Request Routing Module 1000

As shown in FIG. 2B, a Data Subject Access Request Routing Module 1000,according to particular embodiments, is adapted for executing the stepsof: (1) at Step 1050, presenting, by at least one computer processor, afirst webform on a first web site, the first webform being adapted toreceive data subject access requests and to route the requests to afirst designated individual (e.g., an individual who is associated witha first sub-organization of a particular organization—e.g., an employeeof the first sub-organization) for processing (in various embodiments,“presenting a webform on a website” may comprise, for example: (A)providing a button, link, or other selectable indicium on the websitethat, when selected, causes the system to display the webform, or (B)displaying the webform directly on the website); (2) at Step 1100presenting, by at least one computer processor, a second webform on asecond website, the second webform being adapted to receive data subjectaccess requests and to route the requests to a second designatedindividual (e.g., an individual who is associated with a secondsub-organization of a particular organization—e.g., an employee of thesecond sub-organization) for processing; (3) at Step 1150, receiving, byat least one computer processor, via the first webform, a first datasubject access request; (4) at Step 1200, at least partially in responseto the receiving the first data subject access request, automaticallyrouting the first data subject access request to the first designatedindividual for handling; (5) at Step 1250, at least partially inresponse to the receiving the second data subject access request,automatically routing the second data subject access request to thesecond designated individual for handling; and (6) at Step 1300,communicating, via a single user interface, a status of both the firstdata subject access request and the second data subject access request.

In particular embodiments: (1) the first website is a website of a firstsub-organization of a particular parent organization; (2) the secondwebsite is a website of a second sub-organization of the particularparent organization; and (3) the computer-implemented method furthercomprises communicating, by at least one computer processor, via asingle user interface, a status of each of said first data subjectaccess request and said second data subject access request (e.g., to anemployee of—e.g., privacy officer of—the parent organization). Asdiscussed in more detail below, this single user interface may displayan indication, for each respective one of the first and second datasubject access requests, of a number of days remaining until a deadlinefor fulfilling the respective data subject access request.

In certain embodiments, the single user interface is adapted tofacilitate the deletion or assignment of multiple data subject accessrequests to a particular individual for handling in response to a singlecommand from a user (e.g., in response to a user first selectingmultiple data subject access requests from the single user interface andthen executing an assign command to assign each of the multiple requeststo a particular individual for handling).

In particular embodiments, the system running the Data Subject AccessRequest Routing Module 1000, according to particular embodiments, may beadapted for, in response to receiving each data subject access request,generating an ID number (e.g., a transaction ID or suitableAuthentication Token) for the first data subject access request, whichmay be used later, by the DSAR requestor, to access information relatedto the DSAR, such as personal information requested via the DSAR, thestatus of the DSAR request, etc. To facilitate this, the system may beadapted for receiving the ID number from an individual and, at leastpartially in response to receiving the ID number from the individual,providing the individual with information regarding status of the datasubject access request and/or information previously requested via thedata subject access request.

In particular embodiments, the system may be adapted to facilitate theprocessing of multiple different types of data subject access requests.For example, the system may be adapted to facilitate processing: (1)requests for all personal data that an organization is processing forthe data subject (a copy of the personal data in a commonly used,machine-readable format); (2) requests for all such personal data to bedeleted; (3) requests to update personal data that the organization isstoring for the data subject; (4) requests to opt out of having theorganization use the individual's personal information in one or moreparticular ways (e.g., per the organization's standard businesspractices), or otherwise change the way that the organization uses theindividual's personal information; and/or (5) the filing of complaints.

In particular embodiments, the system may execute one or more steps(e.g., any suitable step or steps discussed herein) automatically. Forexample, the system may be adapted for: (1) receiving, from the firstdesignated individual, a request to extend a deadline for satisfying thefirst data subject access request; (2) at least partially in response toreceiving the extension request, automatically determining, by at leastone processor, whether the requested extension complies with one or moreapplicable laws or internal policies; and (3) at least partially inresponse to determining that the requested extension complies with theone or more applicable laws or internal policies, automaticallymodifying the deadline, in memory, to extend the deadline according tothe extension request. The system may be further adapted for, at leastpartially in response to determining that the requested extension doesnot comply with the one or more applicable laws or internal policies,automatically rejecting the extension request. In various embodiments,the system may also, or alternatively, be adapted for: (1) at leastpartially in response to determining that the requested extension doesnot comply with the one or more applicable laws or internal policies,automatically modifying the length of the requested extension to complywith the one or more applicable laws or internal policies; and (2)automatically modifying the deadline, in memory, to extend the deadlineaccording to the extension request.

In various embodiments, the system may be adapted for: (1) automaticallyverifying an identity of a particular data subject access requestorplacing the first data subject access request; (2) at least partially inresponse to verifying the identity of the particular data subject accessrequestor, automatically obtaining, from a particular data model, atleast a portion of information requested in the first data subjectaccess request; and (3) after obtaining the at least a portion of therequested information, displaying the obtained information to a user aspart of a fulfillment of the first data subject access request. Theinformation requested in the first data subject access request may, forexample, comprise at least substantially all (e.g., most or all) of theinformation regarding the first data subject that is stored within thedata model.

In various embodiments, the system is adapted for: (1) automaticallyverifying, by at least one computer processor, an identity of aparticular data subject access requestor placing the first data subjectaccess request; and (2) at least partially in response to verifying theidentity of the particular data subject access requestor, automaticallyfacilitating an update of personal data that an organization associatedwith the first webform is processing regarding the particular datasubject access requestor.

Similarly, in particular embodiments, the system may be adapted for: (1)automatically verifying, by at least one computer processor, an identityof a particular data subject access requestor placing the first datasubject access request; and (2) at least partially in response toverifying the identity of the particular data subject access requestor,automatically processing a request, made by the particular data subjectaccess requestor, to opt out of having the organization use theparticular data subject access requestor's personal information in oneor more particular ways.

The system may, in various embodiments, be adapted for: (1) providing,by at least one computer processor, a webform creation tool that isadapted for receiving webform creation criteria from a particular user,the webform creation criteria comprising at least one criterion from agroup consisting of: (A) a language that the form will be displayed in;(B) what information is to be requested from data subjects who use thewebform to initiate a data subject access request; and (C) who any datasubject access requests that are received via the webform will be routedto; and (2) executing the webform creation tool to create both the firstwebform and the second webform.

In light of the discussion above, although the Data Subject AccessRequest Routing Module 1000 is described as being adapted to, in variousembodiments, route data subject access requests to particularindividuals for handling, it should be understood that, in particularembodiments, this module may be adapted to process at least part of, orall of, particular data subject access requests automatically (e.g.,without input from a human user). In such cases, the system may or maynot route such automatically-processed requests to a designatedindividual for additional handling or monitoring. In particularembodiments, the system may automatically fulfill all or a portion of aparticular DSAR request, automatically assign a transaction ID and/orauthentication token to the automatically fulfilled transaction, andthen display the completed DSAR transaction for display on a systemdashboard associated with a particular responsible individual that wouldotherwise have been responsible for processing the DSAR request (e.g.,an individual to whom the a webform receiving the DSAR would otherwiseroute DSAR requests). This may be helpful in allowing the human user tolater track, and answer any questions about, the automatically-fulfilledDSAR request.

It should also be understood that, although the system is described, invarious embodiments, as receiving DSAR requests via multiple webforms,each of which is located on a different website, the system may, inother embodiments, receive requests via only a single webform, orthrough any other suitable input mechanism other than a webform (e.g.,through any suitable software application, request via SMS message,request via email, data transfer via a suitable API, etc.)

In various embodiments, the system may be adapted to access informationneeded to satisfy DSAR requests via one or more suitable data models.Such data models include those that are described in greater detail inU.S. patent application Ser. No. 15/996,208, filed Jun. 1, 2018, which,as noted above, is incorporated herein by reference. In variousembodiments, the system is adapted to build and access such data modelsas described in this earlier-filed U.S. patent application.

As an example, in fulfilling a request to produce, modify, or delete,any of a data subject's personal information that is stored by aparticular entity, the system may be adapted to access a suitable datamodel to identify any personal data of the data subject that iscurrently being stored in one or more computer systems associated withthe particular entity. After using the data model to identify the data,the system may automatically process the data accordingly (e.g., bymodifying or deleting it, and/or sharing it with the DSAR requestor). Inparticular embodiments, the system may be configured to automaticallyprocess a plurality of data subject access requests (DSARs) (e.g., 2, 3,4, 5, 6, 7, or more DSARs) simultaneously (e.g., in response to a singleor multiple commends from one or more users).

DSAR Prioritization Module

A DSAR Prioritization Module, according to various embodiments, isadapted for (1) executing the steps of receiving a data subject accessrequest; (2) at least partially in response to receiving the datasubject access request, obtaining metadata regarding a data subject ofthe data subject access request; (3) using the metadata to determinewhether a priority of the DSAR should be adjusted based on the obtainedmetadata; and (4) in response to determining that the priority of theDSAR should be adjusted based on the obtained metadata, adjusting thepriority of the DSAR.

The operation of various embodiments of the various software modulesabove is described in greater detail below. It should be understood thatthe various steps described herein may be executed, by the system, inany suitable order and that various steps may be omitted, or other stepsmay be added in various embodiments.

Operation of Example Implementation

FIGS. 3-43 are screen shots that demonstrate the operation of aparticular embodiment. FIGS. 3-6 show a graphical user interface (GUI)of an example webform construction tool. FIG. 3 shows a user working todesign a webform called “Web_form_1”. As may be understood from thevertical menu shown on the left-hand side of the screen, the webformconstruction tool allows users to design a webform by: (1) specifyingthe details of the form (via the “Form Details” tab); (2) defining thefields that will be displayed on the webform (via the “Webform Fields”tab); (3) defining the styling of the webform (via the “Form Styling”tab); and (4) defining various settings associated with the webform (viathe “Settings” tab). As shown in FIGS. 4-6, the user may also specifytext to be displayed on the webform (e.g., via a “Form Text” tab).

FIG. 4 shows that, by selecting the “Form Details” tab, the user maydefine which answers a requestor will be able to specify on the webformin response to prompts for information regarding what type of individualthey are (customer, employee, etc.) and what type of request they aremaking via the webform. Example request types include: (1) a request forall personal data that an organization is processing for the datasubject (a copy of the personal data in a commonly used,machine-readable format); (2) a request for all such personal data to bedeleted; (3) a request to update personal data that the organization isstoring for the data subject; (4) a request to opt out of having theorganization use the individual's personal information in one or moreparticular ways (e.g., per the organization's standard businesspractices); (5) file a complaint; and/or (6) other.

FIG. 5 shows that, by selecting the “Settings” tab, the user may specifyvarious system settings, such as whether Captcha will be used to verifythat information is being entered by a human, rather than a computer.

FIG. 6 shows that, by selecting the Form Styling tab, the user mayspecify the styling of the webform. The styling may include, forexample: (1) a header logo; (2) header height; (3) header color; (4)body text color; (5) body text size; (6) form label color; (7) buttoncolor; (8) button text color; (9) footer text color; (10) footer textsize; and/or any other suitable styling related to the webform.

In other embodiments, the system is configured to enable a user tospecify, when configuring a new webform, what individual at a particularorganization (e.g., company) will be responsible for responding torequests made via the webform. The system may, for example, enable theuser to define a specific default sub-organization (e.g., within theorganization) responsible for responding to DSAR's submitted via the newwebform. As such, the system may be configured to automatically route anew DSAR made via the new webform to the appropriate sub-organizationfor processing and fulfillment. In various embodiments, the system isconfigured to route one or more various portions of the DSAR to one ormore different sub-organizations within the organization for handling.

In particular embodiments, the system may include any suitable logic fordetermining how the webform routes data subject access requests. Forexample, the system may be adapted to determine which organization orindividual to route a particular data subject access request to based,at least in part, on one or more factors selected from a groupconsisting of: (1) the data subject's current location; (2) the datasubject's country of residence; (3) the type of request being made; (4)the type of systems that contain (e.g., store and/or process) the user'spersonal data (e.g., in ADP, Salesforce, etc.); or any other suitablefactor.

In particular embodiments, the system is configured to enable a usergenerating webforms to assign multiple webforms to multiple differentrespective suborganizations within an organization. For example, anorganization called ACME, Inc. may have a website for each of aplurality of different brands (e.g., sub-organizations) under which ACMEsells products (e.g., UNICORN Brand T-shirts, GRIPP Brand Jeans, etc.).As may be understood in light of this disclosure, each website for eachof the particular brands may include an associated webform forsubmitting DSAR's (either a webform directly on the web site, or onethat is accessible via a link on the website). Each respective webformmay be configured to route a DSAR made via its associated brand websiteto a particular sub-organization and/or individuals within ACME forhandling DSAR's related to the brand.

As noted above, after the user uses the webform construction tool todesign a particular webform for use on a particular web page, thewebform construction tool generates code (e.g., HTML code) that may bepasted into the particular web page to run the designed webform page. Inparticular embodiment, when pasted into the particular web page, thecode generates a selectable button on the web page that, when selected,causes the system to display a suitable DSAR request webform.

FIG. 7 shows the privacy webpage of a company (e.g., the ACMEcorporation). As shown in this figure, a requestor may submit a DSAR byselecting a “Submit a Privacy Related Request” button on the web page.

FIG. 8 shows a webform that is displayed after a requestor selects the“Submit a Privacy Related Request” button on the privacy webpage of FIG.7. As may be understood from this figure, the requestor may complete thewebform by specifying which type of user they are, and what type ofrequest they are making. The webform also asks the requestor to provideenough personal information to confirm their identity (e.g., and fulfillthe request). As shown in this figure, the system may prompt a usersubmitting a DSAR to provide information for the user such as, forexample: (1) what type of requestor the user is (e.g., employee,customer, etc.); (2) what the request involves (e.g., requesting info,opting out, deleting data, updating data, etc.); (3) first name; (4)last name; (5) email address; (6) telephone number; (7) home address;(8) one or more other pieces of identifying information; and/or (9) oneor more details associated with the request. FIG. 9 shows an examplepopulated version of the webform.

As shown in FIG. 10, after a requestor completes the webform and selectsa “submit” indicia, the system displays a message to the requestorindicating that their DSAR has been successfully submitted. The systemalso displays a Request ID associated with the request. In response tothe requestor successfully submitting the request, the system may alsosend an email (or other suitable communication) to the requestorconfirming the request. An example of a suitable confirmation email isshown in FIG. 11.

In various embodiments, the system includes a dashboard that may be usedby various individuals within an organization (e.g., one or more privacyofficers of an organization) to manage multiple DSAR requests. Asdiscussed above, the dashboard may display DSAR's submitted,respectively, to a single organization, any of multiple differentsub-organizations (divisions, departments, subsidiaries etc.) of aparticular organization, and/or any of multiple independentorganizations. For example, the dashboard may display a listing ofDSAR's that were submitted from a parent organization and from theparent organization's U.S. and European subsidiaries. This may beadvantageous, for example, because it may allow an organization tomanage all DSAR requests of all of its sub-organizations (and/or otherrelated organizations) centrally.

FIGS. 12-23, 25-27, 29-34, and 41-43 depict various exampleuser-interface screens of a DSAR request-management dashboard. As may beunderstood from FIG. 12, after an appropriate user (e.g., a privacyofficer associated with a particular organization) logs into the system,the system may display a Data Subject Request Queue that may, forexample, display a listing of all data subject access requests that theappropriate individual has been designated to process. As shown in FIG.12, each data subject access request may be represented by a respectiverow of information that includes: (1) an ID number for the request; (2)the name of the data subject who has submitted the request; (3) thestatus of the request; (4) the number of days that are left to respondto the request (e.g., according to applicable laws and/or internalprocedures); (5) an indication as to whether the deadline to respond tothe request has been extended; (6) a creation date of the request; (7)an indication of the type of requestor that submitted the request(customer, employee, etc.); (8) the name of the individual who has beenassigned to process the request (e.g., the respondent). This screen mayalso include selectable “Edit” and “Filter” buttons that respectivelyfacilitate acting on and filtering the various requests displayed on thepage.

As shown in FIG. 13, in response to a respondent selecting the editbutton while a particular DSAR is highlighted, the system displays adropdown menu allowing the respondent to select between taking thefollowing actions: (1) verify the request; (2) assign the request toanother individual; (3) request an extension; (4) reject the request; or(5) suspend the request.

FIGS. 14 and 15 show a message that the system displays to therespondent in response to the respondent selecting the “verify” option.As shown in this figure, the system prompts the respondent to indicatewhether they are sure that they wish to authenticate the request. Thesystem also presents an input field where the respondent can enter textto be displayed to the requestor along with a request for the requestorto provide information verifying that they are the data subjectassociated with the request. After the respondent populates the inputfield, they may submit the request by selecting a “Submit” button.

In particular embodiments, the input field may enable the respondent toprovide one or more supporting reasons for a decision, by therespondent, to authenticate the request. The respondent may also uploadone or more supporting documents (such as an attachment). The supportingdocuments or information may include, for example, one or more documentsutilized in confirming the requestor's identity, etc.

In response to the respondent selecting the Submit button, the systemchanges the status of the request to “In Progress” and also changes thecolor of the request's status from orange to blue (or from any othersuitable color to any different suitable color)—see FIG. 16. The systemalso generates and sends a message (e.g., an electronic or papermessage) to the requestor asking them to submit information verifyingthe request. The message may include the text that the respondententered in the text box of FIG. 14.

As shown in FIGS. 17-19, in response to a respondent selecting the“Edit” button and then selecting the “Assign” indicia from the displayeddropdown menu, the system displays a Request Assignment interface thatallows a respondent to indicate who the request should be assigned to.For example, the respondent may indicate that they will be handling therequest, or assign the request to another suitable individual, who may,for example, then be designated as the respondent for the request. Ifthe respondent assigns the request to another individual for handling,the respondent may also provide an email address or other correspondenceinformation for the individual. The Request Assignment interfaceincludes a comment box for allowing a respondent to add a message to theindividual that the assignment will be assigned to regarding theassignment. In response to the respondent selecting the “Assign” button,the system assigns the request to the designated individual forhandling. If the request has been assigned to another, designatedindividual, the system automatically generates and sends a message(e.g., an electronic message such as an email or SMS message) to thedesignated individual informing them of the assignment.

As shown in FIGS. 20-22, in response to a respondent selecting the“Edit” button and then selecting the “Reject” indicia from the displayeddropdown menu, the system displays a Reject Request interface. Thisinterface includes a comment box for allowing a respondent to add amessage to the requestor as to why the request was rejected. In responseto the respondent selecting the “Submit” button, the system changes thestatus of the request to “Rejected” and changes the color of therequest's status indicator to red (See FIG. 23). The system may alsoautomatically generate a message (e.g., an electronic or paper message)to the requestor notifying them that their request has been rejected anddisplaying the text that the respondent entered into the Reject Requestinterface of FIG. 22. An example of such a message is shown in FIG. 24.

As shown in FIGS. 25-26, in response to a respondent selecting the“Edit” button and then selecting the “Request Extension” indicia fromthe displayed dropdown menu, the system displays a Request Extensioninterface. This includes a text box for allowing a user to indicate thenumber of days for which they would like to extend the current deadlinefor responding to the request. For example, the dialog box of FIG. 26shows the respondent requesting that the current deadline be extended by90 days. In response to the respondent entering a desired extensionduration and selecting the “Submit” button, the system updates thedeadline in the system's memory (e.g., in an appropriate data structure)to reflect the extension. For instance, in the example of FIG. 26, thesystem extends the deadline to be 90 days later than the currentdeadline. As shown in FIG. 27, the system also updates the “Days Left toRespond” field within the Data Subject Request Queue to reflect theextension (e.g., from 2 days from the current date to 92 days from thecurrent date). As shown in FIG. 28, the system may also generate anappropriate message (e.g., an electronic, such as an email, or a papermessage) to the requestor indicating that the request has been delayed.This message may provide a reason for the delay and/or an anticipatedupdated completion date for the request.

In particular embodiments, the system may include logic forautomatically determining whether a requested extension complies withone or more applicable laws or internal policies and, in response,either automatically grant or reject the requested extension. Forexample, if the maximum allowable time for replying to a particularrequest is 90 days under the controlling laws and the respondentrequests an extension that would result in the fulfillment of therequest 91 or more days from the date that the request was submitted,the system may automatically reject the extension request. In variousembodiments, the system may also communicate, to the respondent (e.g.,via a suitable electronic message or text display on a system userinterface) an explanation as to why the extension request was denied,and/or a maximum amount of time (e.g., a maximum number of days) thatthe deadline may be extended under the applicable laws or policies. Invarious embodiments, if the system determines that the requestedextension is permissible under the applicable laws and/or policies, thesystem may automatically grant the extension.

In other embodiments, the system may be configured to automaticallymodify a length of the requested extension to conform with one or moreapplicable laws and/or policies. For example, if the request was for a90-day extension, but only a 60 day extension is available under theapplicable laws or regulations, the system may automatically grant a60-day extension rather than a 90 day extension. The system may beadapted to also automatically generate and transmit a suitable message(e.g., a suitable electronic or paper communication) notifying them ofthe fact that the extension was granted for a shorter, specified periodof time than requested.

As shown in FIGS. 29-34, a respondent may obtain additional detailsregarding a particular request by selecting (e.g., clicking on) therequest on the Data Subject Request Queue screen. For example, FIG. 30shows a Data Subject Request Details screen that the system displays inresponse to a respondent selecting the “Donald Blair” request on theuser interface screen of FIG. 35. As shown in FIG. 30, the Data SubjectRequest Details screen shows all correspondence between the organizationand the requesting individual regarding the selected data subject accessrequest. As may be understood from FIG. 31, when a respondent selects aparticular correspondence (e.g., email), the system displays thecorrespondence to the respondent for review or other processing.

As shown in FIG. 32, in various embodiments, the system may provide aselectable “Reply” indicia that allows the respondent to reply toparticular correspondence from an individual. As may be understood fromthis figure, in response to the respondent selecting the “Reply”indicia, the system may display a dropdown menu of various standardreplies. For example, the dropdown menu may provide the option ofgenerating a reply to the requestor indicating that the request has beenrejected, is pending, has been extended, or that the request has beencompleted.

As shown in FIG. 33, in response to the respondent selecting “Reply asCompleted”, the system may generate a draft email to the requestorexplaining that the request has been completed. The respondent may thenedit this email and send the edited correspondence (e.g., via email) tothe requestor by selecting a “Send as Complete” indicia. As shown inFIG. 34, the system may, in response, display an indicator adjacent thecorrespondence indicating that the correspondence included a replyindicating that the request was complete. This may be useful in allowingindividuals to understand the contents of the correspondence withouthaving to open it.

FIG. 35 shows an example email automatically generated by the system inresponse to the respondent selecting “Reply as Completed” on the screenshown in FIG. 32. As shown in FIG. 35, the correspondence may include asecure link that the requestor may select to access the data that wasrequested in the DSAR. In particular embodiments, the link is a link toa secure website, such as the website shown in FIG. 36, that providesaccess to the requested data (e.g., by allowing a user to download a.pdf file, or other suitable file, that includes the requested data). Asshown in FIG. 36, the website may require multiple pieces of data toverify that the requestor is permitted to access the site. For example,in order to access the website, the requestor may be required to provideboth the unique ID number of the request, and an authentication token,which the system may send to the user via email—See FIGS. 37 and 38.

FIGS. 39-43 are computer screen shots that depict additional userinterfaces according to various embodiments.

Additional Concepts

Intelligent Prioritization of DSAR's

In various embodiments, the system may be adapted to prioritize theprocessing of DSAR's based on metadata about the data subject of theDSAR. For example, the system may be adapted for: (1) in response toreceiving a DSAR, obtaining metadata regarding the data subject; (2)using the metadata to determine whether a priority of the DSAR should beadjusted based on the obtained metadata; and (3) in response todetermining that the priority of the DSAR should be adjusted based onthe obtained metadata, adjusting the priority of the DSAR.

Examples of metadata that may be used to determine whether to adjust thepriority of a particular DSAR include: (1) the type of request, (2) thelocation from which the request is being made, (3) current sensitivitiesto world events, (4) a status of the requestor (e.g., especially loyalcustomer), or (5) any other suitable metadata.

In various embodiments, in response to the system determining that thepriority of a particular DSAR should be elevated, the system mayautomatically adjust the deadline for responding to the DSAR. Forexample, the system may update the deadline in the system's memoryand/or modify the “Days Left to Respond” field (See FIG. 13) to includea fewer number of days left to respond to the request. Alternatively, orin addition, the system may use other techniques to convey to arespondent that the request should be expedited (e.g., change the colorof the request, send a message to the respondent that they shouldprocess the request before non-prioritized requests, etc.)

In various embodiments, in response to the system determining that thepriority of a particular DSAR should be lowered, the system mayautomatically adjust the deadline for responding to the DSAR by addingto the number of days left to respond to the request.

Automatic Deletion of Data Subject Records Based on Detected Systems

In particular embodiments, in response a data subject submitting arequest to delete their personal data from an organization's systems,the system may: (1) automatically determine where the data subject'spersonal data is stored; and (2) in response to determining the locationof the data (which may be on multiple computing systems), automaticallyfacilitate the deletion of the data subject's personal data from thevarious systems (e.g., by automatically assigning a plurality of tasksto delete data across multiple business systems to effectively deletethe data subject's personal data from the systems). In particularembodiments, the step of facilitating the deletion may comprise, forexample: (1) overwriting the data in memory; (2) marking the data foroverwrite; (2) marking the data as free (e.g., and deleting a directoryentry associated with the data); and/or (3) any other suitable techniquefor deleting the personal data. In particular embodiments, as part ofthis process, the system uses an appropriate data model (see discussionabove) to efficiently determine where all of the data subject's personaldata is stored.

Automatic Determination of Business Processes that Increase Chance ofDeletion Requests

In various embodiments, the system is adapted to store, in memory, a logof DSAR actions. The system may also store, in memory, additionalinformation regarding the data subjects of each of the requests. Thesystem may use this information, for example, to determine whichbusiness processes are most commonly associated with a data subjectsubmitting a request to have their personal information deleted from theorganization's systems. The organization may then use this informationto revise the identified business processes in an effort to reduce thenumber of deletion requests issued by data subjects associated with thebusiness processes.

As a particular example, the system may analyze stored information todetermine that a high number (e.g., 15%) of all participants in acompany's loyalty program submit requests to have their personalinformation deleted from the company's systems. In response to makingthis determination, the system may issue an electronic alert to anappropriate individual (e.g., a privacy officer of the company),informing them of the high rate of members of the company's loyaltyprogram issuing personal data delete requests. This alert may prompt theindividual to research the issue and try to resolve it.

Automated Data Subject Verification

In various embodiments, before a data subject request can be processed,the data subject's identity may need to be verified. In variousembodiments, the system provides a mechanism to automatically detect thetype of authentication required for a particular data subject based onthe type of Data Subject Access Request being made and automaticallyissues a request to the data subject to verify their identity againstthat form of identification. For example, a subject rights request mightonly require two types of authentication, but a deletion request mayrequire four types of data to verify authentication. The system mayautomatically detect which is type of authentication is required basedon the DSAR and send an appropriate request to the data subject toverify their identity.

Stated more particularly, when processing a data subject access request,the system may be configured to verify an identity of the data subjectprior to processing the request (e.g., or as part of the processingstep). In various embodiments, confirming the identity of the datasubject may, for example, limit a risk that a third-party or otherentity may gain unlawful or unconsented to access to the requestor'spersonal data. The system may, for example, limit processing andfulfillment of requests relating to a particular data subject torequests that are originated by (e.g., received from) the particulardata subject. When processing a data subject access request, the systemmay be configured to use various reasonable measures to verify theidentity of the data subject who requests access (e.g., in particular inthe context of online services and online identifiers). In particularembodiments, the system is configured to substantially automaticallyvalidate an identity of a data subject when processing the data subjectaccess request.

For example, in particular embodiments, the system may be configured tosubstantially automatically (e.g., automatically) authenticate and/orvalidate an identity of a data subject using any suitable technique.These techniques may include, for example: (1) one or more credit-basedand/or public- or private-information-based verification techniques; (2)one or more company verification techniques (e.g., in the case of abusiness-to-business data subject access request); (3) one or moretechniques involving integration with a company's employeeauthentication system; (4) one or more techniques involving a company's(e.g., organization's) consumer portal authentication process; (5) etc.Various exemplary techniques for authenticating a data subject arediscussed more fully below.

In particular embodiments, when authenticating a data subject (e.g.,validating the data subject's identity), the system may be configured toexecute particular identity confirmation steps, for example, byinterfacing with one or more external systems (e.g., one or morethird-party data aggregation systems). For example, the system, whenvalidating a data subject's identity, may begin by verifying that aperson with the data subject's name, address, social security number, orother identifying characteristic (e.g., which may have been provided bythe data subject as part of the data subject access request) actuallyexists. In various embodiments, the system is configured to interfacewith (e.g., transmit a search request to) one or more credit reportingagencies (e.g., Experian, Equifax, TransUnion, etc.) to confirm that aperson with one or more characteristics provided by the data subjectexists. The system may, for example, interface with such creditreporting agencies via a suitable plugin (e.g., software plugin).Additionally, there might be a verification on behalf of a trustedthird-party system (e.g., the controller).

In still other embodiments, the system may be configured to utilize oneor more other third-party systems (e.g., such as LexisNexis, IDology,RSA, etc.), which may, for example, compile utility and phone bill data,property deeds, rental agreement data, and other public records forvarious individuals. The system may be configured to interface with oneor more such third-party systems to confirm that a person with one ormore characteristics provided by the data subject exists.

After the step of confirming the existence of a person with the one ormore characteristics provided by the data subject, the system may beconfigured to confirm that the person making the data subject accessrequest is, in fact, the data subject. The system may, for example,verify that the requestor is the data subject by prompting the requestorto answer one or more knowledge-based authentication questions (e.g.,out-of-wallet questions). In particular embodiments, the system isconfigured to utilize one or more third-party services as a source ofsuch questions (e.g., any of the suitable third-party sources discussedimmediately above). The system may use third-party data from the one ormore third-party sources to generate one or more questions. These one ormore questions may include questions that a data subject should know ananswer to without knowing the question ahead of time (e.g., one or moreprevious addresses, a parent or spouse name and/or maiden name, etc.).

FIG. 46 depicts an exemplary identity verification questionnaire. As maybe understood from this figure, an identity verification questionnairemay include one or more questions whose responses include data that thesystem may derive from one or more credit agencies or other third-partydata aggregation services (e.g., such as previous street addresses,close associates, previous cities lived in, etc.). In particularembodiments, the system is configured to provide these one or morequestions to the data subject in response to receiving the data subjectaccess request. In other embodiments, the system is configured to promptthe data subject to provide responses to the one or more questions at alater time (e.g., during processing of the request). In particular otherembodiments, the system is configured to substantially automaticallycompare one or more pieces of information provided as part of the datasubject access request to one or more pieces of data received from athird-party data aggregation service in order to substantiallyautomatically verify the requestor's identity.

In still other embodiments, the system may be configured to prompt arequestor to provide one or more additional pieces of information inorder to validate the requestor's identity. This information mayinclude, for example: (1) at least a portion of the requestor's socialsecurity number (e.g., last four digits); (2) a name and/or place ofbirth of the requestor's father; (3) a name, maiden name, and/or placeof birth of the requestor's mother; and/or (4) any other informationwhich may be useful for confirming the requestor's identity (e.g., suchas information available on the requestor's birth certificate). In otherembodiments, the system may be configured to prompt the requestor toprovide authorization for the company to check the requestor's socialsecurity or other private records (e.g., credit check authorization,etc.) to obtain information that the system may use to confirm therequestor's identity. In other embodiments, the system may prompt theuser to provide one or more images (e.g., using a suitable mobilecomputing device) of an identifying document (e.g., a birth certificate,social security card, driver's license, etc.).

The system may, in response to a user providing one or more responsesthat matches information that the system receives from one or morethird-party data aggregators or through any other suitable background,credit, or other search, substantially automatically authenticate therequestor as the data subject. The system may then continue processingthe data subject's request, and ultimately fulfill their request.

In particular embodiments, such as embodiments in which the requestorincludes a business (e.g., as in a business to business data subjectaccess request), the system may be configured to authenticate therequesting business using one or more company verification techniques.These one or more company validation techniques may include, forexample, validating a vendor contract (e.g., between the requestingbusiness and the company receiving the data subject access request);receiving a matching token, code, or other unique identifier provided bythe company receiving the data subject access request to the requestingbusiness; receiving a matching file in possession of both the requestingbusiness and the company receiving the data subject access request;receiving a signed contract, certificate (e.g., digital or physical), orother document memorializing an association between the requestingbusiness and the company receiving the data subject access request;and/or any other suitable method of validating that a particular requestis actually made on behalf of the requesting business (e.g., byrequesting the requesting business to provide one or more pieces ofinformation, one or more files, one or more documents, etc. that mayonly be accessible to the requesting business).

In other embodiments, the system may be configured to authenticate arequest via integration with a company's employee or customer (e.g.,consumer) authentication process. For example, in response to receivinga data subject access request that indicates that the data subject is anemployee of the company receiving the data subject access request, thesystem may be configured to prompt the employee to login to thecompany's employee authentication system (e.g., Okta, Azure, AD, etc.)In this way, the system may be configured to authenticate the requestorbased at least in part on the requestor successfully logging into theauthentication system using the data subject's credentials. Similarly,in response to receiving a data subject access request that indicatesthat the data subject is a customer of the company receiving the datasubject access request, the system may be configured to prompt thecustomer to login to an account associated with the company (e.g., via aconsumer portal authentication process). In a particular example, thismay include, for example, an Apple ID (for data subject access requestsreceived by Apple). In this way, the system may be configured toauthenticate the requestor based at least in part on the requestorsuccessfully logging into the authentication system using the datasubject's credentials. In some embodiments, the system may be configuredto require the requestor to login using two-factor authentication orother suitable existing employee or consumer authentication process.

Data Subject Blacklist

In various embodiments, a particular organization may not be required torespond to a data subject access request that originates (e.g., isreceived from) a malicious requestor. A malicious requestor may include,for example: (1) a requestor (e.g., an individual) that submitsexcessive or redundant data subject access requests; (2) a group ofrequestors such as researchers, professors, students, NGOs, etc. thatsubmit a plurality of requests for reasons other than those reasonsprovided by policy, law, etc.; (3) a competitor of the company receivingthe data subject access request that is submitting such requests to tieup the company's resources unnecessarily; (4) a terrorist or otherorganization that may spam requests to disrupt the company's operationand response to valid requests; and/or (5) any other request that mayfall outside the scope of valid requests made for reasons proscribed bypublic policy, company policy, or law. In particular embodiments, thesystem is configured to maintain a blacklist of such maliciousrequestors.

In particular embodiments, the system is configured to track a source ofeach data subject access request and analyze each source to identifysources from which: (1) the company receives a large volume of requests;(2) the company receives a large number of repeat requests; (3) etc.These sources may include, for example: (1) one or more particular IPaddresses; (2) one or more particular domains; (3) one or moreparticular countries; (4) one or more particular institutions; (5) oneor more particular geographic regions; (6) etc. In various embodiments,in response to analyzing the sources of the requests, the system mayidentify one or more sources that may be malicious (e.g., are submittingexcessive requests).

In various embodiments, the system is configured to maintain a databaseof the identified one or more sources (e.g., in computer memory). Inparticular embodiments, the database may store a listing of identities,data sources, etc. that have been blacklisted (e.g., by the system). Inparticular embodiments, the system is configured to, in response toreceiving a new data subject access request, cross reference the requestwith the blacklist to determine if the requestor is on the blacklist oris making the request from a blacklisted source. The system may then, inresponse to determining that the requestor or source is blacklisted,substantially automatically reject the request. In particularembodiments, the blacklist cross-referencing step may be part of therequestor authentication (e.g., verification) discussed above. Invarious embodiments, the system may be configured to analyze requestdata on a company by company basis to generate a blacklist. In otherembodiments, the system may analyze global data (e.g., all datacollected for a plurality of companies that utilize the data subjectaccess request fulfillment system) to generate the blacklist.

In particular embodiments, the system may be configured to fulfill datasubject access requests for the purpose of providing a data subject withinformation regarding what data the company collects and for whatpurpose, for example, so the data subject can ensure that the company iscollecting data for lawful reasons. As such, the system may beconfigured to identify requestors and other sources of data requeststhat are made for other reasons (e.g., one or more reasons that wouldnot obligate the company to respond to the request). These reasons mayinclude, for example, malicious or other reasons such as: (1) researchby an academic institution by one or more students or professors; (2)anticompetitive requests by one or more competitors; (3) requests bydisgruntled former employees for nefarious reasons; (4) etc.

In particular embodiments, the system may, for example, maintain adatabase (e.g., in computer memory) of former employees. In otherembodiments, the system may, for example: (1) identify a plurality of IPaddresses associated with a particular entity (e.g., academicorganization, competitor, etc.); and (2) substantially automaticallyreject a data subject access request that originates from the pluralityof IP addresses. In such embodiments, the system may be configured toautomatically add such identified IP addresses and/or domains to theblacklist.

In still other embodiments, the system is configured to maintain alisting of blacklisted names of particular individuals. These mayinclude, for example, one or more individuals identified (e.g., by anorganization or other entity) as submitting malicious data subjectaccess requests).

FIG. 47 depicts a queue of pending data subject access requests. Asshown in this figure, the first three listed data subject accessrequests are new and require verification before processing andfulfillment can begin. As shown in this figure, a user (e.g., such as aprivacy officer or other privacy controller) may select a particularrequest, and select an indicia for verifying the request. The user mayalso optionally select to reject the request. FIG. 48 depicts anauthentication window that enables the user to authenticate a particularrequest. In various embodiments, the user may provide an explanation ofwhy the user is authenticating the request (e.g., because the requestorsuccessfully completed on or more out-of-wallet questions or for anyother suitable reason). The user may further submit one or moreattachments to support the verification. In this way, the system may beconfigured to document that the authentication process was performed foreach request (e.g., in case there was an issue with improperlyfulfilling a request, the company could show that they are followingprocedures to prevent such improper processing). In other embodiments,the system may enable the user to provide similar support when rejectinga request (e.g., because the requestor was blacklisted, made excessiverequests, etc.).

Data Subject Access Request Fulfillment Cost Determination

In various embodiments, as may be understood in light of thisdisclosure, fulfilling a data subject access request may be particularlycostly. In some embodiments, a company may store data regarding aparticular data subject in multiple different locations for a pluralityof different reasons as part of a plurality of different processing andother business activities. For example, a particular data subject may beboth a customer and an employee of a particular company or organization.Accordingly, in some embodiments, fulfilling a data subject accessrequest for a particular data subject may involve a plurality ofdifferent information technology (IT) professionals in a plurality ofdifferent departments of a particular company or organization. As such,it may be useful to determine a cost of a particular data subject accessrequest (e.g., particularly because, in some cases, a data subject isentitled to a response to their data subject access request as a matterof right at no charge).

In particular embodiments, in response to receiving a data subjectaccess request, the system may be configured to: (1) assign the requestto at least one privacy team member; (2) identify one or more IT teamsrequired to fulfill the request (e.g., one or more IT teams associatedwith one or more business units that may store personal data related tothe request); (3) delegate one or more subtasks of the request to eachof the one or more IT teams; (4) receive one or more time logs from eachindividual involved in the processing and fulfillment of the datasubject access request; (5) calculate an effective rate of eachindividual's time (e.g., based at least in part on the individual'ssalary, bonus, benefits, chair cost, etc.); (6) calculate an effectivecost of fulfilling the data subject access request based at least inpart on the one or more time logs and effective rate of each of theindividual's time; and (7) apply an adjustment to the calculatedeffective cost that accounts for one or more external factors (e.g.,overhead, etc.) in order to calculate a cost of fulfilling the datasubject access request.

In particular embodiments, the system is configured to substantiallyautomatically track an amount of time spent by each individual involvedin the processing and fulfillment of the data subject access request.The system may, for example, automatically track an amount of timebetween each individual opening and closing a ticket assigned to them aspart of their role in processing or fulfilling the data subject accessrequest. In other embodiments, the system may determine the time spentbased on an amount of time provided by each respective individual (e.g.,the individual may track their own time and submit it to the system).

In various embodiments, the system is configured to measure a cost ofeach particular data subject access request received, and analyze one ormore trends in costs of, for example: (1) data subject access requestsover time; (2) related data subject access requests; (3) etc. Forexample, the system may be configured to track and analyze cost andtime-to-process trends for one or more social groups, one or morepolitical groups, one or more class action groups, etc. In particular,the system may be configured to identify a particular group from whichthe system receives particularly costly data subject access request(e.g., former and/or current employees, members of a particular socialgroup, members of a particular political group, etc.).

In particular embodiments, the system may be configured to utilize datasubject access request cost data when processing, assigning, and/orfulfilling future data subject access requests (e.g., from a particularidentified group, individual, etc.). For example, the system may beconfigured to prioritize requests that are expected to be less costlyand time-consuming (e.g., based on past cost data) over requestsidentified as being likely more expensive. Alternatively, the system mayprioritize more costly and time-consuming requests over less costly onesin the interest of ensuring that the system is able to respond to eachrequest in a reasonable amount of time (e.g., within a time required bylaw, such as a thirty day period, or any other suitable time period).

Customer Satisfaction Integration with Data Subject Access Requests

In various embodiments, the system may be configured to collect customersatisfaction data, for example: (1) as part of a data subject accessrequest submission form; (2) when providing one or more results of adata subject access request to the data subject; or (3) at any othersuitable time. In various embodiments, the customer satisfaction datamay be collected in the form of a suitable survey, free-form responsequestionnaire, or other suitable satisfaction data collection format(e.g., thumbs up vs. thumbs down, etc.).

FIG. 49 depicts an exemplary customer satisfaction survey that may beincluded as part of a data subject access request form, provided alongwith the results of a data subject access request, provided in one ormore messages confirming receipt of a data subject access request, etc.As shown in the figure, the customer satisfaction survey may relate tohow likely a customer (e.g., a data subject) is to recommend the company(e.g., to which the data subject has submitted the request) to a friend(e.g., or colleague). In the example shown in FIG. 49, the satisfactionsurvey may relate to a Net Promoter score (NPS), which may indicate aloyalty of a company's customer relationships. Generally speaking, theNet Promoter Score may measure a loyalty that exists between a providerand a consumer. In various embodiments, the provider may include acompany, employer, or any other entity. In particular embodiments, theconsumer may include a customer, employee, or other respondent to an NPSsurvey.

In particular embodiments, the question depicted in FIG. 49 is theprimary question utilized in calculating a Net Promoter Score (e.g.,“how likely is it that you would recommend our company/product/serviceto a friend or colleague?”). In particular embodiments, the question ispresented with responses ranging from 0 (not at all likely) to 10(extremely likely). In particular embodiments, the question may includeany other suitable scale. As may be understood from FIG. 49, the systemmay be configured to assign particular categories to particular ratingson the 10 point scale. The system may be configured to track and storeresponses provided by consumers and calculate an overall NPS score forthe provider. The system may be further configured to generate a visualrepresentation of the NPS score, including a total number of responsesreceived for each particular score and category as shown in FIG. 49.

In various embodiments, the system may be configured to measure datarelated to any other suitable customer satisfaction method (e.g., inaddition to NPS). By integrating a customer satisfaction survey with thedata subject access request process, the system may increase a number ofconsumers that provide one or more responses to the customersatisfaction survey. In particular embodiments, the system is configuredto require the requestor to respond to the customer satisfaction surveyprior to submitting the data subject access request.

CONCLUSION

Although embodiments above are described in reference to various datasubject access fulfillment systems, it should be understood that variousaspects of the system described above may be applicable to otherprivacy-related systems, or to other types of systems, in general.

While this specification contains many specific embodiment details,these should not be construed as limitations on the scope of anyinvention or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularinventions. Certain features that are described in this specification inthe context of separate embodiments may also be implemented incombination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment may also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination may in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems maygenerally be integrated together in a single software product orpackaged into multiple software products. In addition, it should beunderstood that terms such as “in some embodiments”, “in variousembodiments”, and “in certain embodiments” are intended to indicate thatthe stated features may be implemented in any suitable embodimentdescribed herein.

Many modifications and other embodiments of the invention will come tomind to one skilled in the art to which this invention pertains havingthe benefit of the teachings presented in the foregoing descriptions andthe associated drawings. Therefore, it is to be understood that theinvention is not to be limited to the specific embodiments disclosed andthat modifications and other embodiments are intended to be includedwithin the scope of the appended claims. Although specific terms areemployed herein, they are used in a generic and descriptive sense onlyand not for the purposes of limitation.

What is claimed is:
 1. A computer system for processing a request todelete personal data from a plurality of computing devices associatedwith a particular organization, the computer system comprising: one ormore computer processors; computer memory embodied in one or morecomputer storage locations operatively coupled to the one or morecomputer processors that stores particular computer code, wherein thecomputer system is configured for: receiving a plurality of deletepersonal data requests, each delete personal data request of theplurality of delete personal data requests being a request, from arespective data subject, to delete personal data associated with thedata subject from one or more computer storage locations; and at leastpartially in response to receiving each respective delete personal datarequest: automatically using a data model to identify at least onecomputer storage location of the one or more computer storage locationson which first respective personal data associated with the respectivedata subject is stored, wherein: the data model: defines the at leastone computer storage location utilized in the storage of a plurality ofdifferent items of personal data for each respective data subject aspart of a processing activity; stores information regarding respectivestorage locations of the plurality of different items of personal datafor each respective data subject; and comprises a respective datainventory for each of the one or more computer storage locations andmaps one or more relationships between one or more aspects of each datainventory and the one or more computer storage locations; andautomatically using the data model to identify the at least one computerstorage location comprises using a unique identifier associated with therespective data subject in combination with the data model to identifythe at least one computer storage location as storing the firstrespective personal data associated with the respective data subject;and at least partially in response to identifying the at least onecomputer storage location as storing the first respective personal dataassociated with the respective data subject, facilitating the deletionof the first respective personal data from the at least one computerstorage location, wherein using the unique identifier associated withthe respective data subject in combination with the data model toidentify the at least one computer storage location as storing the firstrespective personal data associated with the respective data subjectcomprises: analyzing each respective data inventory to identify one ormore data inventory attributes associated with each of the one or morecomputer storage locations; and scanning the one or more data inventoryattributes using the unique identifier to determine the at least onecomputer storage location.
 2. The computer system of claim 1, whereinthe system is further configured for concurrently processing at leastfive of the plurality of delete personal data requests in an automatedmanner.
 3. The computer system of claim 2, wherein the data model storesinformation regarding respective storage locations of a plurality ofdifferent respective items of personal data for each of a plurality ofindividuals other than the respective data subject.
 4. The computersystem of claim 1, wherein the system is further configured forfacilitating the execution of multiple delete personal data requests inresponse to a single command from a user.
 5. The computer system ofclaim 1, wherein the computer system is configured for at leastpartially in response to receiving each respective delete personal datarequest of the plurality of delete personal data requests: obtainingmetadata regarding each respective data subject; using the metadata todetermine whether a priority of each respective delete personal datarequest should be adjusted based on the metadata; in response todetermining that the priority of a particular delete personal datarequest should be adjusted based on the metadata, adjusting the priorityof the particular delete personal data request, wherein the metadatacomprises metadata selected from a group consisting of: (A) a locationfrom which each respective delete personal data request was made; (B)one or more current sensitivities to world events; and (C) a status ofeach respective data subject; and fulfilling the respective requestaccording to the adjusted priority of the respective request.
 6. Thecomputer system of claim 1, wherein facilitating the deletion of thefirst respective personal data from the at least one computer storagelocation comprises the first respective personal data in computer memoryassociated with the at least one computer storage location.
 7. Thecomputer system of claim 1, wherein the unique identifier associatedcomprises a first unique identifier generated in response to receivingconsent from the respective data subject for processing of the firstrespective personal data by the particular organization.
 8. The computersystem of claim 1 wherein: the data model further defines at least onetransfer location to which the plurality of different items of personaldata are transferred from the at least one computer storage location;and facilitating the deletion of the first respective personal data fromthe at least one computer storage location comprises facilitating thedeletion of the first respective personal data from both at least onecomputer storage location and the at least one transfer location.
 9. Thecomputer system of claim 8, wherein the one or more computer storagelocations comprise the at least one storage location.
 10. A computersystem for processing a request to delete personal data from a pluralityof computing devices associated with a particular organization, thecomputer system comprising: one or more computer processors; computermemory embodied in one or more computer storage locations operativelycoupled to the one or more computer processors that stores particularcomputer code, wherein the computer system is configured for: receiving,by the one or more computer processors, a plurality of delete personaldata requests, each delete personal data request being a request, from arespective data subject, to delete personal data associated with thedata subject; and at least partially in response to receiving eachrespective request of the plurality of requests: automaticallyidentifying, by the one or more computer processors, at least onecomputing device of the one or more computer storage locations on whichthe personal data associated with the respective data subject is stored,wherein identifying the at least one computing device comprises:accessing, by the one or more computer processors, a data modeldefining:  at least one storage location where a plurality of pieces ofpersonal data are stored as part of a processing activity;  at least onetransfer location to which the plurality of pieces of personal data aretransferred from the at least one storage location as part of theprocessing activity; and using a unique identifier associated with therespective data subject, in combination with the data model, to identifythe personal data associated with the respective data subject; and inresponse to identifying, by the one or more computer processors, the atleast one computing device on which the personal data associated withthe respective data subject is stored, automatically facilitatingdeletion of the personal data associated with the respective datasubject from the at least one storage location and the at least onetransfer location, wherein: the data model comprises a respective datainventory for each of the one or more computer storage locations andmaps one or more relationships between one or more aspects of each datainventory and the one or more computer storage locations; using theunique identifier associated with the respective data subject incombination with the data model to identify the personal data associatedwith the respective data subject comprises:  analyzing each respectivedata inventory to identify one or more data inventory attributesassociated with each of the one or more computer storage locations; and scanning the one or more data inventory attributes using the uniqueidentifier to determine the at least one computing device of the one ormore computer storage locations.
 11. The computer system of claim 10,wherein the at least one computing device comprises both the at leastone storage location and the at least one transfer location.
 12. Thecomputer system of claim 11, wherein the computer system is furtherconfigured for concurrently processing, by the one or more computerprocessors, at least five of the plurality of delete personal datarequests in an automated manner.
 13. The computer system of claim 11,wherein automatically facilitating the deletion of the personal dataassociated with the respective data subject from the at least onestorage location and the at least one transfer location comprisesoverwriting the personal data associated with the respective datasubject in computer memory associated with both the at least one storagelocation and the at least one transfer location.
 14. The computer systemof claim 10, wherein the unique identifier associated with therespective data subject comprises a unique identifier generated inresponse to receiving consent provided by the respective data subjectfor an initial storage of the personal data associated with therespective data subject as part of the processing activity.
 15. Thecomputer system of claim 10, wherein the at least one computing deviceon which the personal data associated with the respective data subjectis stored comprises identifying the at least one computing device usingone or more data modeling means.
 16. The computer system of claim 10,wherein the method further comprises: identifying a first processingactivity under which the respective data subject has previously providedconsent for the collection of personal data; and electronicallyaccessing a first data inventory associated with the first processingactivity, the first data inventory identifying: a first data asset ofthe one or more computer storage locations on which the personal datacollected as part of the first processing activity is stored; transferdata associated with the first data asset; and access data associatedwith the first data asset; and facilitating the deletion of the personaldata associated with the respective data subject from the one or morecomputer storage locations by: automatically assigning a first task todelete the personal data associated with the respective data subjectfrom the first data asset; identifying a second data asset based atleast in part on the transfer data; automatically assigning a secondtask to delete the personal data associated with the respective datasubject from the second data asset; identifying a third data asset basedat least in part on the access data; and automatically assigning a thirdtask to delete the personal data associated with the respective datasubject from the third data asset.
 17. A personal data processing anddeletion system comprising; one or more processors; one or more dataassets that store a plurality of personal data associated with aplurality of data subjects, each piece of the plurality of personal databeing associated with a respective particular processing activity of aplurality of processing activities undertaken by an organization; andcomputer memory, wherein: the computer memory stores one or more datamodels defining one or more data transfers among the one or more dataassets; and the data processing and deletion system is configured for:receiving a first data subject request associated with a first datasubject from a remote computing device, the first data subject requestcomprising a request to delete one or more first pieces of personal datafrom the personal data processing and deletion system, one or more firstpieces of personal data being associated with the first data subject; inresponse to receiving the first data subject request, identifying, basedat least in part on the one or more data models and the plurality ofprocessing activities undertaken by the organization, a respectivestorage location of each of the one or more first pieces of personaldata on the one or more data assets; and in response to identifying therespective storage location of each of the one or more pieces ofpersonal data, automatically facilitating the deletion of each of theone or more first pieces of personal data from each respective storagelocation, wherein: the one or more data models comprise a respectivedata inventory for each of the one or more data assets and maps one ormore relationships between one or more aspects of each data inventoryand the one or more data assets; and the data processing and deletionsystem is further configured for using a unique identifier associatedwith the first data subject in combination with the one or more datamodels to identify the one or more first pieces of personal data datasubject comprises:  analyzing each respective data inventory to identifyone or more data inventory attributes associated with each of the one ormore data assets; and  scanning the one or more data inventoryattributes using the unique identifier to determine the respectivestorage location of each of the one or more first pieces of personaldata on the one or more data assets.
 18. The personal data processingand deletion system of claim 17, wherein automatically facilitating thedeletion of each of the one or more first pieces of personal data fromeach respective storage location comprises overwriting each of the oneor more first pieces of personal data at each respective storagelocation.
 19. The personal data processing and deletion system of claim17, wherein the personal data processing and deletion system is furtherconfigured for concurrently processing, by the one or more processors, aplurality of data subject requests simultaneously.